Mechanism design for spatio-temporal request satisfaction in mobile networks

Mobile agents participating in geo-presence-capable crowdsourcing applications should be presumed rational, competitive, and willing to deviate from their routes if given the right incentive. In this paper, we design a mechanism that takes into consideration this rationality for request satisfaction in such applications. We propose the Geo-temporal Request Satisfaction (GRS) problem to be that of finding the optimal assignment of requests with specific spatio-temporal characteristics to competitive mobile agents subject to spatio-temporal constraints. The objective of the GRS problem is to maximize the total profit of the system subject to our rationality assumptions. We define the problem formally, prove that it is NP-Complete, and present a practical solution mechanism, which we prove to be convergent, and which we evaluate experimentally.National Science Foundation (1012798, 0952145, 0820138, 0720604, 0735974

Incentive Mechanisms for Participatory Sensing: Survey and Research Challenges

Participatory sensing is a powerful paradigm which takes advantage of smartphones to collect and analyze data beyond the scale of what was previously possible. Given that participatory sensing systems rely completely on the users' willingness to submit up-to-date and accurate information, it is paramount to effectively incentivize users' active and reliable participation. In this paper, we survey existing literature on incentive mechanisms for participatory sensing systems. In particular, we present a taxonomy of existing incentive mechanisms for participatory sensing systems, which are subsequently discussed in depth by comparing and contrasting different approaches. Finally, we discuss an agenda of open research challenges in incentivizing users in participatory sensing.Comment: Updated version, 4/25/201

Enrichment of raw sensor data to enable high-level queries

Sensor networks are increasingly used across various application domains. Their usage has the advantage of automated, often continuous, monitoring of activities and events. Ubiquitous sensor networks detect location of people and objects and their movement. In our research, we employ a ubiquitous sensor network to track the movement of players in a tennis match. By doing so, our goal is to create a detailed analysis of how the match progressed, recording points scored, games and sets, and in doing so, greatly reduce the eort of coaches and players who are required to study matches afterwards. The sensor network is highly efficient as it eliminates the need for manual recording of the match. However, it generates raw data that is unusable by domain experts as it contains no frame of reference or context and cannot be analyzed or queried. In this work, we present the UbiQuSE system of data transformers which bridges the gap between raw sensor data and the high-level requirements of domain specialists such as the tennis coach

Topologies for combining the Internet of Things and Serious Games

Serious Games have been established over recent years as a means of utilising gaming for applications other than entertainment.With the emergence of the Internet of Things (IoT) paradigm, a new direction for serious games arises, where data gathered from the physical environment can be utilised towards new novel applications. This literature survey uncovers existing topologies that can be applied for combining IoT with Serious Games. This paper presents findings from extensive research into IoT, Serious Games, Pervasive Games and Gamification, IoT topologies and Wireless Sensor Networks (WSN), to identify the requirements of a topology for Serious Games and IoT. By understanding the topological requirements for combining IoT and Serious Games, the development process is reduced, allowing for the advancement in the mentioned field. Three topologies are presented for combining IoT with Serious Games and a detailed topology for developing a Serious Game that monitors student attendance is presented. Also included, is an insight into the new paradigm of Smart Serious Games (SSGs). This paper will aid future research and development in SSGs determine effective network topologies

Pervasive Games in a Mote-Enabled Virtual World Using Tuple Space Middleware

Pervasive games are a new and exciting field where the user experience benefits from the blending of real and virtual elements. Players are no longer confined to computer screens. Rather, interactions with devices embedded within the real world and physical movements become an integral part of the gaming experience. Several prototypes of pervasive games have been proposed by both industry and academia. However, in such games the issues arising from the integration of players and real world, the management of the context surrounding the players, and the need for communication and distributed coordination are often addressed in an ad-hoc fashion. Therefore, the underlying software fabric is often not reusable, ultimately slowing down the diffusion of pervasive games. In this paper we describe the design and implementation of a pervasive game on top of TinyLIME, a middleware system supporting data sharing among mobile and embedded devices. By illustrating the design of a pervasive game we developed, we argue concretely that the programming abstractions supported by TinyLIME greatly simplify the data and context management characteristics of pervasive games, and provide an effective and reusable building block for their development. TinyLIME was originally designed to support applications where mobile users collect data from sensors scattered in the physical environment. We build upon this capability to put forth a second contribution, namely, the use of wireless sensor devices (or motes) as a computing platform for pervasive games. Besides reporting physical data for the sake of the game, we use motes to store information relevant to the game plot, e.g., virtual objects. Motes are typically very small in size, and therefore can be hidden in the environment, enhancing the sense of immersion in a virtual world. To the best of our knowledge, this original use of wireless sensor devices is novel in the scientific and gaming literature. Furthermore, it is naturally supported by TinyLIME, yielding a unified programming abstraction that spans the heterogeneous gaming platform we propose

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Rational coordination of crowdsourced resources for geo-temporal request satisfaction

Existing mobile devices roaming around the mobility field should be considered as useful resources in geo-temporal request satisfaction. We refer to the capability of an application to access a physical device at particular geographical locations and times as GeoPresence, and we pre- sume that mobile agents participating in GeoPresence-capable applica- tions should be rational, competitive, and willing to deviate from their routes if given the right incentive. In this paper, we define the Hitch- hiking problem, which is that of finding the optimal assignment of re- quests with specific spatio-temporal characteristics to competitive mobile agents subject to spatio-temporal constraints. We design a mechanism that takes into consideration the rationality of the agents for request sat- isfaction, with an objective to maximize the total profit of the system. We analytically prove the mechanism to be convergent with a profit com- parable to that of a 1/2-approximation greedy algorithm, and evaluate its consideration of rationality experimentally.Supported in part by NSF Grants; #1430145, #1414119, #1347522, #1239021, and #1012798